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Predictive Modeling of US Winter Apparel Sales using Time Series Forecasting Method

机译:使用时间序列预测方法对美国冬季服装销售进行预测建模

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Fashion and apparel sales have always been an interesting aspect of study due to the immense number of controllable and uncontrollable variables that contributes to the total sales. In order to develop a sound predictive model for forecasting apparel sales a lot of factors can be incorporated to enhance the results and minimize the forecast error. This paper will present a Time Series Forecasting model of US Apparel and accessories sales for the winter season. This model is generated to shed the light on the unexpected loss incurred by retailers for the winter season of 2015 by incorporating weather variation as an influencer on the sales. This paper is also going to discuss some important managerial approaches which empower firms to deal better with unforeseen variabilities.
机译:时装和服装的销售一直是研究中一个有趣的方面,因为可控变量和不可控变量的数量众多,它们构成了总销售额。为了开发用于预测服装销售的合理预测模型,可以结合很多因素来增强结果并最大程度地减少预测误差。本文将介绍冬季美国服装和配件销售的时间序列预测模型。通过将天气变化作为影响销售的因素,该模型的产生是为了揭示零售商在2015年冬季造成的意外损失。本文还将讨论一些重要的管理方法,这些方法可以使公司更好地应对不可预见的变化。

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